Altered Expression of Fibronectin and Collagens I and IV in Multiple Myeloma and Monoclonal Gammopathy of Undetermined Significance
Bibliographic record
Abstract
Multiple myeloma (MM) is an incurable B-cell malignancy that arises in the bone marrow (BM). The malignant cells within the BM have extensive interaction with the structural components of their microenvironment. It has been previously shown that the interactions between MM cells and the BM extracellular matrix (ECM) proteins contribute to drug resistance. To understand the underlying causes of adhesion-mediated drug resistance in MM, the components of human BM ECM available for interactions with MM cells must be characterized. We analyzed the expression and localization of fibronectin, laminin, and collagens I and IV in the core biopsies of normal donors and patients with monoclonal gammopathy of undetermined significance (MGUS) or MM. In addition, we compared the patterns of ECM expression in MM patients with low-, mid-, and high-level plasmacytosis of the BM. Although expression of laminin was the same for all groups tested, levels of fibronectin and collagen I were reduced in MM patients with high-level plasmacytosis. Expression of collagen IV in the BM of MGUS and MM patients was higher than in the BM from normal donors. Compared with the plasma cells isolated from the patients with low- and mid-level plasmacytosis, sorted CD138(+) plasma cells from MM patients with high-level plasmacytosis overexpressed collagen IV. Our findings show that, compared with normal controls, the ECM composition of the bone, endosteum, and BM is aberrant in patients with MM, further establishing ECM as a key player in the MM disease process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".